code: def freq_of_dicts(
      dicts: List[Dict],
      serializer=lambda d: frozenset(d.items()),
      deserializer=dict,
  ) -> DictCount:
      """Count a list of dictionaries (or unhashable types).
  
      This is somewhat annoying because mutable data structures aren't hashable,
      and set/dict keys must be hashable.
  
      Args:
          dicts (List[D]): A list of dictionaries to be counted.
          serializer (D -> S): A custom serialization function. The output type S
              must be hashable. The default serializer converts a dictionary into
              a frozenset of KV pairs.
          deserializer (S -> U): A custom deserialization function. See the
              serializer for information about type S. For dictionaries U := D.
  
      Returns:
          List[Tuple[U, int]]: Returns a list of tuples. Each entry in the list
              is a tuple containing a unique entry from `dicts` and its
              corresponding frequency count.
      """
      freqs = Counter(serializer(d) for d in dicts)
      as_list = []
      for as_set, count in freqs.items():
          as_list.append((deserializer(as_set), count))
      return as_list
  
imports: import logging
  import time
  from collections import Counter
  from functools import reduce
  from typing import Dict, List
  from ray._private.gcs_utils import PlacementGroupTableData
  from ray.autoscaler._private.constants import AUTOSCALER_MAX_RESOURCE_DEMAND_VECTOR_SIZE, AUTOSCALER_REPORT_PER_NODE_STATUS
  from ray.autoscaler._private.util import DictCount, LoadMetricsSummary, NodeIP, ResourceDict
  from ray.core.generated.common_pb2 import PlacementStrategy
label_desc: Use image node_id 2 for calling a global function with example usage: freq_of_dicts(dicts, serializer, deserializer) and returns: as_list